A cardiac medical device may monitor cardiac electrical signals for many purposes. A cardiac control instrument analyzes cardiac signals to determine how well the cardiovascular system is performing. As a result of this analysis, the instrument responds to some predetermined signal characteristics by automatically initiating control operations. A cardiac signal measurement device analyzes cardiac signals to illuminate diagnostic information within a sensed cardiac waveform. The time sequence of cardiac signal amplitudes which are sensed by a device constitutes the morphology, or shape, of the cardiac waveform. Some components of the cardiac signal with significant diagnostic utility have small amplitudes in relation to other signal elements. Often, important diagnostic information within the cardiac waveform is obscured by noise.
Signal averaging is a technique for detecting low amplitude periodic signals which are obscured by random signals having a much larger amplitude. This technique involves the averaging of multiple occurrences of the periodic waveform. Signal averaging reduces the amplitude of an additive random noise signal by a factor proportional to the inverse of the square root of the number of the signal-averaged heart beats. Signal averaging reduces the influence of beat to beat changes, respiratory variations and other changes not synchronized to the electrocardiogram and allows detection of low amplitude periodic signals otherwise hidden in noise.
These benefits of signal averaging are available only if the analyzing device can temporally align, with extreme accuracy, the cardiac signal components within each cardiac cycle which are periodic and have a period of a single cardiac cycle. The timing marker for each cardiac cycle which defines proper alignment is called a fiducial time. Timing offsets between waveforms from different cardiac cycles will cause the averaged signal to lessen rather than increase the desired signal morphology amplitude.
One method of aligning the waveforms from different cardiac cycles is to correlate the sensed and sampled waveform from the current cardiac cycle with the stored signal average, in a manner described in greater detail below. The resulting correlation coefficients for the samples provide alignment information in two ways; first, they are utilized to determine whether the current signal is sufficiently similar to the averaged signal to perform averaging in this cycle; and, second, they are used to determine the position within the averaged signal at which to add each current sample. The correlation coefficients for the samples are mutually compared with the coefficients of the other samples to determine the maximum correlation coefficient. If the maximum correlation coefficient is too small, the current waveform is too dissimilar to be averaged into the averaged signal. Otherwise, the current waveform is averaged into the averaged signal according to the location of the maximum correlation coefficient for the cycle.
Correlation involves the summation of the products of point-by-point multiplications of two waveform sequences for the purpose of deriving a standard of similarity between the two waveform sequences. Unfortunately, correlation analysis requires such computational complexity that it is impractical in an implanted device. Because the device expends energy on each computational step and correlation requires so many computations, the lifetime of an implanted device performing correlation would be unreasonably short or the battery size too large for practical usage.
One modified technique for performing standard correlation is by multiplying the waveform sequences in a section-by-section manner called piecewise correlation analysis, which provides for a reduction in the number of required computations by limiting the correlation procedure to operate only in the vicinity of the R-wave. In one example of piecewise correlation, a signal processing system defines a representative "normal" signal by measuring a ventricular electrogram signal template when the heart is functioning with a normal sinus rhythm. The system specifies this template by "windowing" the waveform, detecting the QRS complex of the cardiac signal and storing a predetermined number of samples before and after the QRS complex. For example, a waveform window may include 64 samples, which contain the QRS complex and are acquired at a 1000 Hz rate. The system averages a number of these waveform windows for a preset number of cardiac cycles with the QRS complex for each cardiac cycle occurring at the same sample location within the window. After sampling and storing the template waveform, the system samples the ventricular electrogram at the same rate and for the same number of samples as was done when acquiring the template samples. The system correlates these samples with the average sinus rhythm template on a beat-by-beat basis.
The piecewise correlation technique requires that the QRS complexes of the template and the sample electrogram are aligned. In piecewise correlation analysis, accurate template alignment is very important. In practice, alignment errors greater than four to five milliseconds cause a large and unpredictable variability in correlation coefficients. Furthermore, alignment errors frequently are not recognized since a sensing determination aligned on some feature other than the R-wave may still result in a high correlation output.
Reliable template alignment is not a simple procedure. For example, a system which aligns R-waves according to a measured point of maximum intracardiac electrogram (IEGM) amplitude or corresponding to the peak derivative of the signal does not provide adequate alignment due to the large variability in amplitude and slope of the signal waveform. Signal processing of the cardiac signal to clarify the position of the R-wave using a variety of search windows and filtering techniques is helpful for particular signal morphologies but no single alignment procedure is adequate for all patients. The wide variability in cardiac signal morphologies for different patients and also for different times for the same patient cause these alignment difficulties.
Furthermore, a system which performs window alignment based on the peak cardiac signal amplitude is susceptible to errors from T-wave sensing. Occasional patients may display T-waves which are consistently larger in amplitude than R-waves. Consequently, windows may align on the T-wave or may align on the R- and T-waves in alternating cardiac cycles. Systems which align the template and sample signals based on the location of the sensed peak derivative commonly err from five to ten milliseconds because of the noisy nature of derivative signals. When combined with low pass filtering, alignment by peak derivative sensing improves somewhat but remains unacceptable.
The small size of the piecewise correlation window which is necessary to provide the computational efficiency for an implantable device leads to an additional source of alignment error. As the device performs piecewise correlation over a single cardiac cycle it may detect multiple peaks, possibly caused by T-wave sensing or detection of multiple peaks associated with the R-wave.
Full scanning correlation, in which a continuously sampled cardiac signal is correlated with a template sequence having a predetermined length smaller than the duration of the shortest possible cardiac cycle, avoids the alignment problems inherent in piecewise correlation. Unfortunately, full scanning correlation requires an excessive number of computations, and therefore too much power drain, for an implantable device.
It is, therefore, a primary object of the present invention to provide a system for accurately determining fiducial times for aligning cardiac electrical waveforms in signal averaging applications.
It is a further object of the present invention to provide for processing of cardiac electrical signal data in a compressed form, thereby reducing the computational and energy requirements of the apparatus.
Further objects and advantages of this invention will become apparent as the following description proceeds.